Computational strategies for analyzing data in gene expression microarray experiments.

摘要: Microarray analysis has become a widely used method for generating gene expression data on genomic scale. Microarrays have been enthusiastically applied in many fields of biological research, even though several open questions remain about the such data. A wide range approaches are available computational analysis, but no general consensus exists as to standard microarray protocol. Consequently, choice technique is crucial element depending both and goals experiment. Therefore, basic understanding bioinformatics required optimal experimental design meaningful interpretation results. This review summarizes some common themes DNA including normalization detection differential expression. Algorithms demonstrated by analyzing cDNA from an experiment monitoring T helper cells. Several biology strategies, along with their relative merits, overviewed potential areas additional research discussed. The goal provide framework applying evaluating strategies. Solid knowledge informatics contributes implementation more efficient protocols given obtained through experiments.